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DOE OSTI2022

Data Assimilation using Non-invasive Monte Carlo Sensitivity Analysis of Reactor Kinetics Parameters [Slides]

Sensitivity coefficients of prompt neutron decay constant (α) and effective delayed neutron fraction (β eff ) to Pu-239 nuclear data were calculated using a newly available tool (ACEtk). Uncertainty calculations showed the following trends: (1) The prompt neutron decay constant can be used to reduce nuclear data-induced uncertainty in Pu-239(n,f) and (2) the effective delayed neutron fraction can be used to effectively reduce nuclear data-induced uncertainty in Pu-239 total fission $\tilde{v}$. Sensitivity/uncertainty analysis can be used to determine optimal experiment/detector setup to identify compensating errors in nuclear data. Upcoming work includes investigating other nuclide-reaction pairs and response sensitivities, such as Δ$\rho$, neutron leakage spectra, and reaction rate measurements to constrain nuclear data of interest.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2023

DuraMAT Technology Scouting Report: Assessing Module Reliability Risks Associated with Projected Technological Changes

Maintaining the reliability of photovoltaic (PV) modules in the face of rapidly changing technology is critical to maximizing solar energy's contribution to global decarbonization. Our presentation describes expected changes in PV technology and their impacts on performance and reliability. We leverage PV market reports, interviews with PV researchers and other industry stakeholders, and peer-reviewed literature to narrow the multitude of possible changes into a manageable set of 11 impactful trends likely to be incorporated in near-term crystalline-silicon module designs. We group the trends into four categories (module architecture, interconnect technologies, bifacial modules, and cell technology) and explore the drivers behind the changes, their interactions, and associated reliability risks and benefits. Our analysis identifies specific areas that would benefit from accelerating the PV reliability learning cycle, to assess emerging module products and designs more accurately. We recommend that researchers continue tracking module technologies and their reliability implications so efforts can be focused on the most impactful trends. As the rapid technological turnover continues, it is also critical to incorporate fundamental knowledge into models that can predict module reliability. Predictive capabilities complete the PV reliability learning cycle-reducing the time required to assess new designs and mitigating the risks associated with large-scale deployment of new products.

bifacial↗

NASA NTRS2015

The Impact of Trends in the Large Scale Atmospheric Circulation on Mediterranean Surface Turbulent Heat Fluxes

Interannual variations of latent heat fluxes (LHF) and sensible heat fluxes (SHF) over the Mediterranean for the boreal winter season (DJF) show positive trends during 1958-2011. Comparison of correlations between the heat fluxes and the intensity and location of the Azores High (AH), and the NAO and East Atlantic-West Russia (EAWR) teleconnections, along with analysis of composites of surface temperature, humidity and wind fields for different teleconnection states, demonstrates that variations of the AH are found to explain the heat flux changes more successfully than the NAO and the EAWR. Trends in sea level pressure and longitude of the Azores High during DJF show a strengthening, and an eastward shift. DJF Azores High pressure and longitude are shown to co-vary such that variability of the Azores High occurs along an axis defined by lower pressure and westward location at one extreme, and higher pressure and eastward location at the other extreme. The shift of the Azores High from predominance of the low/west state to the high/east state induces trends in Mediterranean Sea surface winds, temperature and moisture. These, combined with sea surface warming trends, produce trends in wintertime Mediterranean Sea sensible and latent heat fluxes.

heat flux↗

DOE OSTI2023

A multifrequency characterization of the extragalactic hard X-ray sky

Context: Nowadays, we know that the origin of the cosmic X-ray background (CXB) is mainly due to the integrated emission of active galactic nuclei. Therefore, in order to obtain a precise estimate of the contribution of different source classes to the CXB, it is crucial to achieve full characterization of the hard-X ray sky. Aims: We present a multifrequency analysis of all sources listed in the third release of the Palermo Swift-BAT hard X-ray catalog (3PBC) with the goal of (i) identifying and classifying the largest number of sources adopting multifrequency criteria, with particular emphasis on extragalactic populations and (ii) extracting sources belonging to the class of Seyfert galaxies to present here the release of the second version of the Turin-SyCAT. Methods: We outline a classification scheme based on radio, infrared (IR), and optical criteria that allows us to distinguish between unidentified and unclassified hard X-ray sources, as well as to classify those sources belonging to the Galactic and the extragalactic populations. Results: Our revised version of the 3PBC lists 1176 classified, 820 extragalactic, and 356 Galactic sources, as well as 199 unclassified and 218 unidentified sources. According to our analysis, the hard X-ray sky is mainly populated by Seyfert galaxies and blazars. For the blazar population, we report trends between the hard X-ray and the gamma-ray emissions based on the fact that a large fraction of them also have a counterpart detected by the Fermi satellite. These trends are all in agreement with the expectations of inverse Compton models which are widely adopted to explain the blazar broadband emission. For the Seyfert galaxies, we present the second version of the Turin-SyCAT, including a total of 633 Seyfert galaxies, with 282 new sources corresponding to an increase of ~80% with respect to the previous release. Comparing the hard X-ray and the infrared emissions of Seyfert galaxies, we confirm that there is no clear difference between the flux distribution of the infrared-to-hard X-ray flux ratio of Seyfert galaxies Type 1 and Type 2. However, there is a significant trend between the mid-IR flux and hard X-ray flux, confirming previous statistical results in the literature. Conclusions: We provide two catalog tables. The first is the revised version of the 3PBC catalog based on our multifrequency analyses. The second catalog table is a release of the second version of the Turin-SyCAT catalog. Finally, we highlight that extensive soft X-ray data are already available in the form of the Swift archive which can be used to search for potential counterparts of unidentified hard X-ray sources. All these datasets will be reduced and analyzed in a forthcoming analysis to determine the precise position of low-energy counterparts in the 0.5–10 keV energy range for 3PBC sources that can be targets of future optical spectroscopic campaigns; this is necessary to obtain their precise classification.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

Utility-Scale Solar, 2023 Edition: Empirical Trends in Deployment, Technology, Cost, Performance, PPA Pricing, and Value in the United States [Slides]

Berkeley Lab’s “Utility-Scale Solar, 2023 Edition” presents analysis of empirical plant-level data from the U.S. fleet of ground-mounted photovoltaic (PV), PV+battery, and concentrating solar-thermal power (CSP) plants with capacities exceeding 5 MWAC (PV plants of 5 MWAC or less, including residential rooftop systems, are covered separately in Berkeley Lab’s companion annual report, Tracking the Sun). Highlights of this year’s update include: -10.4 GWAC of new utility-scale PV capacity came online in 2022, bringing cumulative installed capacity to more than 61.7 GWAC across 46 states. -94% of all new utility-scale PV capacity added in 2022 uses single-axis tracking. -Median installed project costs declined to $\$1.32$/WAC (or $\$1.07$/WDC) in 2022. -Plant-level capacity factors vary widely, from 9% to 35% (on an AC basis), with a sample median of 24%. The report explores drivers of this variation. -Utility-scale PV’s LCOE fell to $\$39$/MWh in 2022 ($\$29$/MWh if factoring in the federal investment tax credit, or ITC). -PPA prices have largely followed the decline in solar’s LCOE over time, but have recently stagnated and even moved slightly higher. Prices from a sample of recent contracts average around $\$20-30$/MWh (levelized) in the West and $\$30-40$/MWh elsewhere in the continental US. -In 2022, solar’s average market value (defined in the report to include only energy and capacity value) rose by 40% to $\$71$/MWh and exceeded average wholesale prices in 4 of the 7 ISOs/RTOs and 11 of 18 other balancing authorities analyzed. -Adding battery storage is one way to increase the value of solar. Our public data file tracks metadata and PPA prices from ~100 PV+battery hybrid projects that are already online or that have secured offtake arrangements. -the end of 2022, there were at least 947 GW of utility-scale solar power capacity within the interconnection queues across the nation, 456 GW of which include batteries. For more information, and to explore related interactive data visualizations, go to utilityscalesolar.lbl.gov.

14 SOLAR ENERGY↗

DOE OSTI2024

Utility-Scale Solar, 2024 Edition: Empirical Trends in Deployment, Technology, Cost, Performance, PPA Pricing, and Value in the United States [Slides]

Berkeley Lab’s “Utility-Scale Solar, 2024 Edition” presents analysis of empirical plant-level data from the U.S. fleet of ground-mounted photovoltaic (PV), PV+battery, and concentrating solar-thermal power (CSP) plants with capacities exceeding 5 MWAC (PV plants of 5 MWAC or less, including residential rooftop systems, are covered separately in Berkeley Lab’s companion annual report, Tracking the Sun). Key findings from this year’s report include: -18.5 GWAC of new utility-scale PV capacity came online in 2023, bringing cumulative installed capacity to more than 80.2 GWAC across 47 states. Installed costs continued to fall in 2023. Relative to 2022, capacity-weighted averages decreased by 8% to -$\$1.43$/WAC (or $\$1.08$/WDC). Costs, based on a 7.1 GWAC sample of 76 plants completed in 2023, have fallen by 75% (averaging 10% annually) since 2010. Plant-level capacity factors vary widely, from 6% to 36% (on an AC basis), with a sample median of 24%. -Levelized cost of energy (LCOE) of new 2023 projects increased slightly to $\$46$/MWh prior to the application of tax credits but continued to fall to $\$31$/MWh when accounting for federal incentives. PPA prices have largely followed the decline in solar’s LCOE over time, but newly signed longer-term PPA prices have increased since 2021, to an average of $\$35$/MWh (levelized, in 2023 dollars). -Solar’s average energy and capacity value (i.e., ability to offset costs of other power generation sources) across the U.S. was $\$45$/MWh in 2023. Solar’s average market value was lowest in CAISO ($\$27$/MWh), the market with the greatest solar generation share, and highest in ERCOT ($\$67$/MWh). -Newer solar projects had greater market value in 2023 than their generation costs, yielding $\$1.1$ billion in benefits. Projects built in 2022 delivered on average $\$15$/MWh more market value than their costs in 2023. -Solar’s combined value from wholesale electricity markets, public health and climate damage reduction were greater than generation costs and incentives, yielding $\$13.7$ billion in net benefits in 2023. We estimate U.S. health benefits of $\$24$/MWh and reduced global climate damages of $\$101$/MWh. -Adding battery storage is one way to increase the value of solar. Deployment of 52 new PV+battery hybrid plants set a record with 5.3 GW installed in 2023. Our public data file tracks metadata and PPA prices from more than 100 PV+battery hybrid projects that are already online or that have secured offtake arrangements. -Looking ahead, a massive pipeline of at least 1,085 GW of solar capacity dominates the nation’s interconnection queues at the end of 2023. Nearly 571 GW, or 53%, of that total was paired with a battery – in CAISO it was a staggering 98%. Historically only 10% of the requested solar capacity is built. -For more information, and to explore related interactive data visualizations, go to utilityscalesolar.lbl.gov.

14 SOLAR ENERGY↗

NASA NTRS1997

Interannual Variability in Soil Trace Gas (CO2, N2O, NO) Fluxes and Analysis of Controllers

Interannual variability in flux rates of biogenic trace gases must be quantified in order to understand the differences between short-term trends and actual long-term change in biosphere-atmosphere interactions. We simulated interannual patterns (1983-1988) of global trace gas fluxes from soils using the NASA Ames model version of CASA (Carnegie-Ames-Stanford Approach) in a transient simulation mode. This ecosystem model has been recalibrated for simulations driven by satellite vegetation index data from the NOAA Advanced Very High Resolution Radiometer (AVHRR) over the mid-1980s. The predicted interannual pattern of soil heterotropic CO2 emissions indicates that relatively large increases in global carbon flux from soils occurred about three years following the strong El Nino Southern Oscillation (ENSO) event of 1983. Results for the years 1986 and 1987 showed an annual increment of +1 Pg (1015 g) C-CO2 emitted from soils, which tended to dampen the estimated global increase in net ecosystem production with about a two year lag period relative to plant carbon fixation. Zonal discrimination of model results implies that 80-90 percent of the yearly positive increments in soil CO2 emission during 1986-87 were attributable to soil organic matter decomposition in the low-latitudes (between 30 N and 30 S). Soils of the northern middle-latitude zone (between 30 N and 60 N) accounted for the residual of these annual increments. Total annual emissions of nitrogen trace gases (N2O and NO) from soils were estimated to vary from 2-4 percent over the time period modeled, a level of variability which is consistent with predicted interannual fluctuations in global soil CO2 fluxes. Interannual variability of precipitation in tropical and subtropical zones (30 N to 20 S appeared to drive the dynamic inverse relationship between higher annual emissions of NO versus emissions of N2O. Global mean emission rates from natural (heterotrophic) soil sources over the period modeled (1983-1988) were estimated at 57.1 Pg C-CO2yr-1, 9.8Tg (1012 g) N-NO yr-1, and 9.7 Tg N-N2O yr-1. Chemical fertilizer contributions to global soil N gas fluxes were estimated at between 1.3 to 7.3 Tg N-NO yr-1, and 1.2 to 4.0 Tg N-N2O yr-1.

Potter, C.↗

NASA NTRS2010

Fingerprinting the Impacts of Aerosols on Long-Term Trends of the Indian Summer Monsoon Regional Rainfall

In this paper, we present corroborative observational evidences from satellites, in-situ observations, and re-analysis data showing possible impacts of absorbing aerosols (black carbon and dust) on subseasonal and regional summer monsoon rainfall over India. We find that increased absorbing aerosols in the Indo-Gangetic Plain in recent decades may have lead to long-term warming of the upper troposphere over northern India and the Tibetan Plateau, enhanced rainfall in northern India and the Himalayas foothill regions in the early part (may-June) of the monsoon season, followed by diminished rainfall over central and southern India in the latter part (July-August) of the monsoon season. These signals which are consistent with current theories of atmospheric heating and solar dimming by aerosol and induced cloudiness in modulating the Indian monsoon, would have been masked by conventional method of using al-India rainfall averaged over the entire monsoon season.

Laul, K. M.↗

NASA NTRS1994

Relationship between ozone and temperature trends in the lower stratosphere: Latitude and seasonal dependences

A one-dimensional radiative transfer model with fixed dynamical heating is used to calculate the approximate latitude and seasonal dependences of lower stratospheric temperature changes associated with observed ozone trends. The spatial and temporal distribution of ozone profile trends in the lower stratosphere is estimated from a combination of Nimbus 7 Solar Backscattered Ultraviolet (SBUV) global measurements of the ozone column below 32 mbar for the period 1979-1990 and balloon ozonesonde profile trends at northern middle latitudes. The calculated temperature trends near 100 mbar compare favorably with those recently derived by Randel and Cobb (1994) using data from Channel 4 of the Microwave Sounding Unit (MSU) on the NOAA operational satellites, although a number of quantitative differences are found. An independent analysis reported here of 100 mbar temperatures derived from northern hemisphere radiosonde data at the Free University of Berlin (FUB) supports the validity of the satellite-derived lower stratospheric temperature trends. These results are therefore generally consistent with the hypothesis that observed lower stratospheric cooling trends are predominantly determined by reductions in radiative heating associated with stratospheric ozone depletion.

Mccormack, John P.↗

NASA NTRS2002

Global Precipitation Analyses at Time Scales of Monthly to 3-Hourly

Global precipitation analysis covering the last few decades and the impact of the new TRMM precipitation observations are discussed. The 20+ year, monthly, globally complete precipitation analysis of the World Climate Research Program's (WCRP/GEWEX) Global Precipitation Climatology Project (GPCP) is used to explore global and regional variations and trends and is compared to the much shorter TRMM (Tropical Rainfall Measuring Mission) tropical data set. The GPCP data set shows no significant trend in precipitation over the twenty years, unlike the positive trend in global surface temperatures over the past century. Regional trends are also analyzed. A trend pattern that is a combination of both El Nino and La Nina precipitation features is evident in the Goodyear data set. This pattern is related to an increase with time in the number of combined months of El Nino and La Nina during the Goodyear period. Monthly anomalies of precipitation are related to ENRON variations with clear signals extending into middle and high latitudes of both hemispheres. The GPCP daily, 1 degree latitude-longitude analysis, which is available from January 1997 to the present is described and the evolution of precipitation patterns on this time scale related to El Nino and La Nina is described. Finally, a TRMM-based Based analysis is described that uses TRMM to calibrate polar-orbit microwave observations from SSM/I and geosynchronous OR observations and merges the various calibrated observations into a final, Baehr resolution map. This TRMM standard product will be available for the entire TRMM period (January Represent). A real-time version of this merged product is being produced and is available at 0.25 degree latitude-longitude resolution over the latitude range from 50 deg. N -50 deg. S. Examples will be shown, including its use in monitoring flood conditions.

Adler, Robert F.↗

NASA NTRS2018

Linking Improvements in Sulfur Dioxide Emissions to Decreasing Sulfate Wet Deposition by Combining Satellite and Surface Observations with Trajectory Analysis

Sulfur dioxide (SO2), a criteria pollutant, and sulfate (SO42) deposition are major environmental concerns in the eastern U.S. and both have been on the decline for two decades. In this study, we use satellite column SO2 data from the Ozone Monitoring Instrument (OMI), and SO42 wet deposition data from the NADP (National Atmospheric Deposition Program) to investigate the temporal and spatial relationship between trends in SO2 emissions and the downward sulfate wet deposition over the eastern U.S. from 2005 to 2015. To establish the relationship between SO2 emission sources and receptor sites, we conducted a Potential Source Contribution Function (PSCF) analysis using HYSPLIT back trajectories for five selected Air Quality System (AQS) sites - (Hackney, OH, Akron, OH, South Fayette, PA, Wilmington, DE, and Beltsville, MD) - in close proximity to NADP sites with large downward SO42 trends since 2005. Back trajectories were run for three summers (JJA) and three winters (DJF) and used to generate seasonal climatology PSCFs for each site. The OMI SO2 and interpolated NADP sulfate deposition trends were normalized and overlapped with the PSCF, to identify the areas that had the highest contribution to the observed drop. The results suggest that emission reductions along the Ohio River Valley have led to decreases in sulfate deposition in eastern OH and western PA (Hackney, Akron and South Fayette). Farther to the east, emission reductions in southeast PA resulted in improvements in sulfate deposition at Wilmington, DE, while for Beltsville, reductions in both the Ohio River Valley and nearby favorably impacted sulfate deposition. For Beltsville, sources closer than 300km from the site contribute roughly 56% observed deposition trends in winter, and 82% in summer, reflecting seasonal changes in transport pattern as well as faster oxidation and washout of sulfur in summer. This suggests that emissions and wet deposition are linked through not only the location of sources relative to the observing sites, but also to photochemistry and the weather patterns characteristic to the region, as evidenced by a west to east shift in the contribution between winter and summer. The method developed here is applicable to other regions with significant trends such as China and India, and can be used to estimate the potential benefits of emission reduction in those areas.

Acid depostion↗

NASA NTRS2018

Linking Improvements in Sulfur Dioxide Emissions to Decreasing Sulfate Wet Deposition By Combining Satellite and Surface Observations With Trajectory Analysis

Sulfur dioxide (SO2), a criteria pollutant, and sulfate (SO42−) deposition are major environmental concerns in the eastern U.S. and both have been on the decline for two decades. In this study, we use satellite column SO2 data from the Ozone Monitoring Instrument (OMI), and SO42− wet deposition data from the NADP (National Atmospheric Deposition Program) to investigate the temporal and spatial relationship between trends in SO2 emissions and the downward sulfate wet deposition over the eastern U.S. from 2005 to 2015. To establish the relationship between SO2 emission sources and receptor sites, we conducted a Potential Source Contribution Function (PSCF) analysis using HYSPLIT back trajectories for five selected Air Quality System (AQS) sites - (Hackney, OH, Akron, OH, South Fayette, PA, Wilmington, DE, and Beltsville, MD) - in close proximity to NADP sites with large downward SO42− trends since 2005. Back trajectories were run for three summers (JJA) and three winters (DJF) and used to generate seasonal climatology PSCFs for each site. The OMI SO2 and interpolated NADP sulfate deposition trends were normalized and overlapped with the PSCF, to identify the areas that had the highest contribution to the observed drop. The results suggest that emission reductions along the Ohio River Valley have led to decreases in sulfate deposition in eastern OH and western PA (Hackney, Akron and South Fayette). Farther to the east, emission reductions in southeast PA resulted in improvements in sulfate deposition at Wilmington, DE, while for Beltsville, reductions in both the Ohio River Valley and nearby favorably impacted sulfate deposition. For Beltsville, sources closer than 300 km from the site contribute roughly 56% observed deposition trends in winter, and 82% in summer, reflecting seasonal changes in transport pattern as well as faster oxidation and washout of sulfur in summer. This suggests that emissions and wet deposition are linked through not only the location of sources relative to the observing sites, but also to photochemistry and the weather patterns characteristic to the region, as evidenced by a west to east shift in the contribution between winter and summer. The method developed here is applicable to other regions with significant trends such as China and India, and can be used to estimate the potential benefits of emission reduction in those areas.

sulfur dioxide emissions↗

NASA NTRS2002

Global Precipitation Analyses at Monthly to 3-HR Time Scales

Global precipitation analysis covering the last few decades and the impact of the new TRMM precipitation observations are discussed. The 20+ year, monthly, globally complete precipitation analysis of the World Climate Research Program's (WCRP/GEWEX) Global Precipitation Climatology Project (GPCP) is used to explore global and regional variations and trends and is compared to the much shorter TRMM(Tropica1 Rainfall Measuring Mission) tropical data set. A trend pattern that is a combination of both El Nino and La Nina precipitation features is evident in the 20-year data set. This pattern is related to an increase with time in the number of combined months of El Nino and La Nina during the 20 year period. Monthly anomalies of precipitation are related to ENSO variations with clear signals extending into middle and high latitudes of both hemispheres. The GPCP daily, 1deg latitude-longitude analysis, which is available from January 1997 to the present is described and the evolution of precipitation patterns on this time scale related to El Nino and La Nina is described. Finally, a TRMM-based 3-hr analysis is described that uses TRMM to calibrate polar-orbit microwave observations from SSM/I and geosynchronous IR observations and merges the various calibrated observations into a final, 3-hr resolution map. This TRMM standard product will soon be available for the entire TRMM period (January 1998- present). A real-time version of this merged product is being produced and is available at 0.25deg latitude-longitude resolution over the latitude range from 50degN-50degS. Images from this data set can be seen at the U.S. TRMM web site (trmm.gsfc.nasa.gov). Examples will be shown, including its use in monitoring flood conditions and relating weather-scale events to climate variations.

Adler, Robert F.↗

DOE OSTI2025

Wind Supply Chain Security: Hardware Enumeration and Analysis

This project, undertaken by Idaho National Laboratory (INL) for the Department of Energy (DOE) Wind Energy Technologies Office (WETO), focused on the enumeration and analysis of six key devices important to wind technologies. The devices analyzed included Beckhoff Bus Terminal Controllers (BK1120 and BC9000), a Beckhoff Economy Built-in Panel PC (CP6231), an N-Tron Managed Industrial Ethernet Switch (711FX3), a Bachmann M1 Gateway, and a Bachmann Smart Power Plant Controller. Device selection was driven by availability and budget constraints, with several components sourced from existing wind farms and others procured through a co-agreement with another WETO-funded project. The project's primary objective was to create a hardware bill of materials (HBOM) for each device, identifying and documenting all components to assess potential security and supply chain risks. A detailed analysis revealed over 750 unique components across the six devices, with 80% successfully identified and accompanied by datasheets. Notably, Texas Instruments emerged as the leading supplier, providing over 16% of the components, followed by ON Semiconductor at 11.3%, Analog Devices at 5.3%, and Renesas Electronics Corp at 4.1%. Other notable vendors included Toshiba Corporation, iC-Haus Corporation, Atmel, Vishay, and STMicroelectronics. The enumeration process involved thorough documentation of each component, including its designation, quantity, identifiers, pin package, description, vendor, model, and country of origin. This process provided valuable insights into the complexity and diversity of the electronic systems within these wind devices. It also highlighted the distinct separation of components between vendors, suggesting a trend of vendor-specific component usage. Key findings from the project emphasized the importance of broadening the scope of vendor analysis in future research to gain a comprehensive understanding of component distribution and commonality. The identification of vendor-specific component usage patterns offers new avenues for research and underscores the significance of continued investigation in this field. Overall, this project provides critical insights into the component composition of wind devices, aiding in the development of improved supply chain management and component sourcing strategies. The results contribute valuable knowledge to the wind technology sector, laying the groundwork for enhanced security and resilience in wind energy systems.

17 - WIND ENERGY↗

NASA NTRS2002

Global Precipitation Analyses (3-Hourly to Monthly) Using TRMM, SSM/I and other Satellite Information

Global precipitation analysis covering the last few decades and the impact of the new TRMM precipitation observations are discussed. The 20+ year, monthly, globally complete precipitation analysis of the World Climate Research Program's (WCRP/GEWEX) Global Precipitation Climatology Project (GPCP) is used to explore global and regional variations and trends and is compared to the much shorter TRMM(Tropical Rainfall Measuring Mission) tropical data set. The GPCP data set shows no significant trend in precipitation over the twenty years, unlike the positive trend in global surface temperatures over the past century. Regional trends are also analyzed. A trend pattern that is a combination of both El Nino and La Nina precipitation features is evident in the 20-year data set. This pattern is related to an increase with time in the number of combined months of El Nino and La Nina during the 20 year period. Monthly anomalies of precipitation are related to ENS0 variations with clear signals extending into middle and high latitudes of both hemispheres. The GPCP daily, 1 deg. latitude-longitude analysis, which is available from January 1997 to the present is described and the evolution of precipitation patterns on this time scale related to El Nino and La Nina is discussed. Finally, a TRMM-based 3-hr analysis is described that uses TRMM to calibrate polar-orbit microwave observations from SSM/I and geosynchronous IR observations and merges the various calibrated observations into a final, 3-hr resolution map. This TRMM standard product will be available for the entire TRMM period (January 1998-present). A real-time version of this merged product is being produced and is available at 0.25 deg. latitude-longitude resolution over the latitude range from 5O deg. N-50 deg. S. Examples are shown, including its use in monitoring flood conditions.

Adler, Robert F.↗

NASA NTRS2022

Midwest Water Resources II: Evaluating Evapotranspiration with NASA Earth Observations and In Situ Observations to Understand Water Balance in Midwest Agriculture

Seasonal water variability in the midwestern United States extensively affects the agricultural community, as it impacts irrigation schedules, growing seasons, and overall ecosystem function. Evapotranspiration (ET) is a critical climatic variable in the water cycle and is used to evaluate spatiotemporal trends in drought and flood conditions. The NASA DEVELOP team partnered with the United States Department of Agriculture (USDA) Midwest Climate Hub, the Minnesota Department of Agriculture, the Illinois State Water Survey, and Michigan State University to compare remotely sensed ET products with in situ observations from January 2001 through December 2020. Remotely sensed actual ET (aET) data were sourced from NASA’s Terra Moderate Resolution Imaging Spectroradiometer (MODIS), and reference ET (refET) data were derived from the Gridded Surface Meteorological (gridMET) dataset. For in situ comparison, aET data were downloaded from the AmeriFlux database while refET data were collected from the Illinois Climate Network and Michigan State University’s Enviro-weather database. For a holistic assessment of ET, this project generated comparisons between remotely sensed and in situ observations, calculated descriptive statistics for validation between refET datasets, and spatially produced statistical validation maps regarding in situ sites. The temporal and spatial gaps of AmeriFlux data limited aET analysis. This comparative assessment of ET products across the Midwest can be used by project partners to assess regional water trends and guide future land management decisions.

Addison Pletcher↗

DOE OSTI2022

Scientific machine learning benchmarks

Deep learning has transformed the use of machine learning technologies for the analysis of large experimental datasets. In science, such datasets are typically generated by large-scale experimental facilities, and machine learning focuses on the identification of patterns, trends and anomalies to extract meaningful scientific insights from the data. In upcoming experimental facilities, such as the Extreme Photonics Application Centre (EPAC) in the UK or the international Square Kilometre Array (SKA), the rate of data generation and the scale of data volumes will increasingly require the use of more automated data analysis. Furthermore, at present, identifying the most appropriate machine learning algorithm for the analysis of any given scientific dataset is a challenge due to the potential applicability of many different machine learning frameworks, computer architectures and machine learning models. Historically, for modelling and simulation on high-performance computing systems, these issues have been addressed through benchmarking computer applications, algorithms and architectures. Extending such a benchmarking approach and identifying metrics for the application of machine learning methods to open, curated scientific datasets is a new challenge for both scientists and computer scientists. Here, we introduce the concept of machine learning benchmarks for science and review existing approaches. As an example, we describe the SciMLBench suite of scientific machine learning benchmarks.

42 ENGINEERING↗

DOE OSTI2022

Temporal variabilities of soil carbon dioxide fluxes from cornfield impacted by temperature and precipitation changes through high-frequent measurement and DAYCENT modelling

Soil carbon dioxide (CO 2 ) emissions from the field of corn (Zea mays L.) play an important role in global warming. This study investigated temporal variability of soil CO 2 fluxes (R s ) with soil temperature (T s ) and moisture (θ) and built DAYCENT models for predicting future impacts of climate changes on R s using the measured high-frequency data. R s trend was tested by Mann–Kendall and Sen Estimator. Predicted R s s under different climate scenarios were compared using Parallel-line Analysis. Herein, the findings indicated that daily R s exponentially increased with T s constrained by θ. During the θ of 27–31%, there was a strong exponential relationship between R s and T s , but the relationship was weaker for the θ of 38–41% and 22–26%. Soil environmental index (SEI, T s × θ) significantly impacted R s with linear regression R s 0.5 = 0.4599 + 0.002059 × SEI in 2008, 2009 and 2011. At the diurnal scale, there were different trends in R s s and relationships among R s and T s and θ in different years. Predicted yearly R s s, root R s s and corn yield in 2014–2049 increased with an increase in temperature scenarios, but the R s s significantly increased as temperature rose by 1°C or higher. Predicted yearly R s s, root R s s and yield reduced with precipitation scenario increase, and the root R s s and yield significantly diminished as precipitation increased by 15 and 30%. Predicted yearly R s from cornfields had a significantly increasing trend. Future research is needed to explore methods for mitigating cornfield R s and evaluating sensitivities of different cropland R s s to temperature changes.

54 ENVIRONMENTAL SCIENCES↗